Machine Operator Integrator Jobs

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Senior Solution Engineer who is accustomed to solving customer’s most complex problems and closing large deals. In this role you will work directly with the sales team and channel partners to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. Field related context As a Snowflake Solution Engineer you must share our passion about reinventing the database space, thrive in a dynamic environment and have the flexibility and willingness to jump in and get things done. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences. IN THIS ROLE YOU WILL GET TO: Present Snowflake technology and vision to executives and technical contributors at prospects and customers Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in rel

Data Engineer Particle41 is seeking a talented Data Engineer to join our team. You will design, build, and maintain data pipelines and infrastructure, support client-facing data visualization, and contribute to AI-assisted data workflows. You will work across the full data lifecycle — from raw ingestion to polished, decision-ready output — in collaboration with cross-functional teams. In This Role You Will Software Development Design, develop, and maintain scalable ETL/ELT pipelines to process large volumes of data from diverse sources. Build and optimize data storage solutions — data lakes and data warehouses — for efficient retrieval and processing. Integrate structured and unstructured data from internal and external systems into a unified view for analysis. Ensure data accuracy, consistency, and completeness through validation, cleansing, and transformation. Maintain clear documentation for data processes, tools, and systems. Data Visualization Build and maintain Tableau dashboards and reports that translate complex datasets into clear, decision-ready visuals. Design data models and extracts optimized for Tableau performance, including live connections and published data sources. Apply data visualization best practices — chart selection, layout, color, and interactivity — to produce client-ready output. Partner with stakeholders to understand reporting needs and translate them into visual solutions. Support ad hoc analysis using Tableau, Python-based charting (matplotlib, seaborn, plotly), or similar tools. AI and Data Support Support AI/ML workflows by building and maintaining the data pipelines that feed model training, inference, and evaluation. Assist with data preparation for LLM and machine learning projects,

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Senior Solution Engineer who is accustomed to solving customer’s most complex problems and closing large deals. In this role you will work directly with the sales team and channel partners to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. Field related context As a Snowflake Solution Engineer you must share our passion about reinventing the database space, thrive in a dynamic environment and have the flexibility and willingness to jump in and get things done. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences. IN THIS ROLE YOU WILL GET TO: Present Snowflake technology and vision to executives and technical contributors at prospects and customers Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in rel

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Principal Solution Engineer who is accustomed to solving customer’s most complex problems and closing large deals. In this role you will work directly with the sales team and channel partners to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. As a Snowflake Solution Engineer you must share our passion about reinventing the database space, thrive in a dynamic environment and have the flexibility and willingness to jump in and get things done. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences. IN THIS ROLE YOU WILL GET TO: Present Snowflake technology and vision to executives and technical contributors at prospects and customers Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in relation to them. Coll

JOB RESPONSIBILITIES A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. We are looking for exceptional students to join us as quantitative researcher interns for Fall 2026, Spring 2027 and Summer 2027. Our interns will work closely with our team, receive comprehensive, in-depth training, and help develop novel signals that may have real impact. You will gain exposure to a variety of activities, which may include: Conducting full pipeline signal research, from ideation, via implementation and backtesting, to eventual application. Adapting and extending existing results in the broad field of machine learning; conducting novel research as needed to potentially develop new signals that may enhance portfolio returns. Analyzing very large data sets to extract features useful for predictive models. Providing research assistance to the team. Helping improve the team’s research infrastructure. DESIRABLE CANDIDATES Masters or PhD candidates in machine learning, computer science, finance, mathematics, or other quantitative disciplines. Demonstrated ability to conduct independent research utilizing machine learning over large, possibly noisy, data sets. Strong analytical and quantitative skills, and detail-oriented mindset. Proficient in Python or C++, and Linux environment. Excellent written and verbal communication skills, willing to proactively engage other team members in helping to foster a highly collaborative, team-oriented research environment. Willing to take ownership of his/her work, working both independently and within a collaborative team. Prior experience in the financial services industry is not required. Commitment to the highest ethical standards. The annual base salary range is $120000.00-$180000.00&n

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning, we would like to talk to you. Role: ALDS Mandate Skills & Competencies: Experience in Programming (Python, R, SQL, NoSQL, Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as NumPy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and c

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning we would like to talk to you. Function : Data Science and Analysis → Data Science / Machine Learning Desired Skills & Competencies: Strong learning acumen Team Management High sense of ownership Ability to work in a fast-paced and deadline-driven environment Loves technology Highly skilled at Data Interpretation Problem solver Good exposure to machine learning concepts and algorithms Must be fluent with any one of Python, R, Java Strong in statistical & machine learning concepts Knowledge of Python Libraries - SciPy, NumPy, Pandas, I Python, Scikit-learn Knowledge of distributed big data processing (PySpark, Jupyter, Linux, AWS) Responsibilities: Hypothesis testing, insights generation, root cause analysis, factor analysis Statistical model (predictive & prescriptive) development using various statistical & machine learning techniques/algorithms Test/train the model, Improve Model accuracy, Monitor model performance Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation

At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else. As a Quantitative Research Intern, you'll spend 10-12 weeks working on research that directly shapes how we understand markets and build trading strategies. You'll collaborate with researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious. This isn't an internship where you observe from the sidelines. Outstanding work has the potential to shape production strategies and generate real, measurable returns. Ideal candidates are quantitatively sharp, practically minded problem solvers, programmers, mathematicians and scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London. What You'll Work On You'll work on real research problems, not simulated exercises, discovering predictive patterns from billions of market events, designing statistical models, and applying machine learning to open research problems. Your work would include: Discovering predictive patterns from billions of market events Designing statistical models that identify trading opportunities Applying probability, optimization and machine learning to open research problems Building AI-powered research agents that accelerate experimentation Developing infrastructure for rapid, large-scale research Designing experiments and backtests to evaluate hypotheses Translating research into production-ready trading signals Exploring new ML, AI and quant finance techniques to find the next source of alpha What You'll Learn Beyond the technical exposure, you'll learn how experienced researchers approach hard problems: breaking them down, questioning assumptions, and deciding based on evidence rather than intuition. You'll be paired with a mentor, reporting manager and buddy, with regular code reviews and feedback through

At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else. As a PhD Quantitative Research Intern, you'll spend 10-12 weeks pointing the research skills you've spent years building at markets. You'll collaborate with researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious. This isn't an internship where you observe from the sidelines, or re-run someone else's experiment. Outstanding work has the potential to shape production strategies and generate real, measurable returns. Ideal candidates are researchers who want to see their methods meet live markets: mathematicians, physicists, statisticians and computer scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London. What You'll Work On You'll work on real research problems, not simulated exercises. Your work would include: Discovering predictive patterns from billions of market events Designing statistical models that identify trading opportunities Applying probability, optimization and machine learning to open research problems Running large-scale simulations and experiments on high-performance research infrastructure Designing experiments and backtests to evaluate hypotheses Building AI-powered research agents that accelerate experimentation Developing infrastructure for rapid, large-scale research Translating research into production-ready trading signals Exploring new ML, AI and quant finance techniques to find the next source of alpha What You'll Learn Beyond the technical exposure, you'll learn what changes when research meets live markets: why a result that would survive peer review can still fail as a trading signal, how costs and capacity constrain an idea that looks clean on paper, and how to tell a model that is right from one that is right for the wrong reason.

At Graviton, we don't believe the best trading strategies come from following established playbooks. They come from asking better questions. Why does a pattern exist? What is driving it? Is it real or just noise? Can it be explained, modelled and turned into an edge? As a Quantitative Researcher, you'll work on those questions every day. You'll investigate market behaviour, develop quantitative models, build and test hypotheses and turn insights into trading strategies, working alongside researchers and technologists in an environment where an idea on a whiteboard can reach live trading quickly. This isn't a role where the answers are in a textbook. The problems are open-ended, the data is enormous, and finding the answers is the job. Ideal candidates are rigorous thinkers who genuinely enjoy mathematics, programming and figuring out things that aren't obvious, based in our Singapore, London, Amsterdam or US offices. What You'll Work On You'll work across quantitative research and systematic trading, taking ideas through the full lifecycle: question, hypothesis, experiment, model, validation, strategy, production. Depending on your team and research interests, your work would include: Discovering predictive patterns and sources of alpha from billions of market events Formulating hypotheses about market behaviour and designing experiments to test them Applying probability, statistics, optimization and machine learning to build predictive models and quantitative signals for systematic trading Designing robust backtests and statistical tests to distinguish genuine signals from noise Working with large and complex datasets to uncover patterns that aren't immediately visible Investigating market microstructure and how markets behave at different timescales Evaluating strategy performance, identifying weaknesses and continuously refining models Developing research infrastructure and AI-powered tools and agents that make experimentation faster and analysis deeper Working c

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Okta & Auth0 Sales Team Auth0 supports Okta’s vision of freeing anyone to safely use any technology by providing a secure, highly available, enterprise-grade platform that secures billions of log-ins every year for Consumer and SaaS applications. As an Account Executive for Auth0 in Korea, you will be the driving force behind our territory growth. This is a versatile role where you will be responsible for the entire market spectrum—from winning high-growth "net-new" logos to cultivating deep, transformative relationships with our most significant existing customers. You will work closely with the Korean partner ecosystem, resellers, and distributors to provide value to Korea’s most mature Product Development teams (Engineering, Product, Security, and Architecture). What you’ll be doing: Strategic Planning: Build and execute a comprehensive territory plan to guide your long-term approach to net-new logo pipeline generation. Revenue Delivery: Consistently meet and exceed revenue targets to support year-over-year growth within the Korean market. Account Strategy: Identify, develop, and execute strategies for high-potential accounts to drive sales opportunities and deliver predictable bookings. Executive Alignment: Target and gain access to C-level leaders and decision-makers, building a robust network of influence within prospect accounts. Stakeholder Management: Highly experienced in running Quarterly Business Reviews (QBRs) and maintaining executive stak

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Senior Analyst, Pricing Strategy & Operations to join our team. This is a Hybrid role, reporting to the Manager, Pricing Strategy & Operations in the Product Management department. We are looking for an analytics professional who can help drive data-backed pricing and monetization decisions for our SaaS business. The role will be responsible for analyzing large and complex datasets, identifying trends and opportunities, and translating insights into clear business recommendations that support revenue growth, discounting, packaging, deal strategy, and overall pricing effectiveness. What you’ll do (Role Expectations) Own and maintain the data tables, structures, and inputs required for pricing, packaging, discounting, cost, and product usage analysis, ensuring accuracy, consistency, and reliability of insights Analyze large datasets across customers, products, usage, revenue, dis

About the Role The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. Key Responsibilities Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unn

NVIDIA is hiring senior engineers to develop its AI platform and more specifically its performance optimizations in deep learning frameworks using JAX, a tool that can differentiate between Python control code and NumPy code. Our goal is to deliver a polished, fast, modular and coordinated platform to handle data, training and analysis for a wide range of deep learning solutions using JAX. To achieve this and provide an excellent user experience, you have strong programming skills and excellent system design skills. You should have excellent communication and planning skills for this role. Come join us to build the next generation of tooling that will advance the numerical computing and machine learning research around the world! What you will be doing: Play meaningful role in NVIDIA's effort in contributing to JAX. Design and implement JAX core components and drive peak performance on NVIDIA products. Work with AI applied researchers and leaders to build future-proof models Build tools that will increase the efficiency of teams developing AI-based systems. Work to bridge the gap between the latest in numerical computing, simulation and deep learning research and their applications in real world products. What we need to see: BS in Computer Science or Computer Engineering or related field (or equivalent experience). 6+ years relevant experience. C/C++ and Python programming. Experience with machine learning frameworks and their internals (e.g. PyTorch, TensorFlow, scikit-learn, etc.). Proven ability developing customer-facing solutions, balancing feature requests and bugs. Proven technical foundation in CPU and GPU architectures, numeric libraries, modular software design. Highly motivated with excellent ver

NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We're looking for a Senior Performance Compiler Engineer to join our team and work on the open-source Triton compiler project. This opportunity involves working with new technologies and using compilers to improve AI performance on NVIDIA GPUs. Your work will enable breakthroughs in large language models, agents, and other high-impact AI applications, accelerating both training and inference. You will be immersed in a diverse, supportive environment where everyone is inspired to do their best work, pushing the limits of what's possible. What you’ll be doing: Investigating the latest and future NVIDIA GPU hardware architecture and programming models. Working on the frontier of AI by understanding advanced algorithms (like attention sinks and MoEs) and numerics (like block-scaled floating point) to identify new opportunities for optimization. Designing and implementing compiler technology using MLIR to optimize high-level kernel descriptions (written in Triton's Python DSL), with a focus on generating efficient, low-level GPU code. When vital, you'll also be able to use inline PTX to hand-tune critical code paths and extract peak performance from the hardware. Engaging in a dynamic, iterative process of optimization—sometimes starting with the kernel, sometimes with the compiler—to find the most efficient path to peak performance. Collaborating with teams across NVIDIA, including hardware architects and the CUDA compiler team, t